code: def _weight_opacity(weight, weight_range):
      # type: (float, float) -> str
      """Return opacity value for given weight as a string."""
      min_opacity = 0.8
      if np.isclose(weight, 0) and np.isclose(weight_range, 0):
          rel_weight = 0.0
      else:
          rel_weight = abs(weight) / weight_range
      return "{:.2f}".format(
          min_opacity + (1 - min_opacity) * rel_weight
      )
  
imports: from __future__ import absolute_import
  from itertools import groupby
  from typing import List, Optional, Tuple
  import numpy
  from jinja2 import Environment, PackageLoader
  from eli5 import _graphviz
  from eli5.base import Explanation, TargetExplanation, FeatureWeights, FeatureWeight
  from eli5.utils import max_or_0
  from .utils import format_signed, format_value, format_weight, has_any_values_for_weights, replace_spaces, should_highlight_spaces
  from .None import fields
  from .features import FormattedFeatureName
  from .trees import tree2text
  from .text_helpers import prepare_weighted_spans, PreparedWeightedSpans
label_desc: Use image node_id 6 for calling a global function with example usage: _weight_opacity(weight, weight_range) and returns: str